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Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study.
- Source :
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Journal of cardiovascular computed tomography [J Cardiovasc Comput Tomogr] 2024 Jan-Feb; Vol. 18 (1), pp. 11-17. Date of Electronic Publication: 2023 Nov 10. - Publication Year :
- 2024
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Abstract
- Background: In the last 15 years, large registries and several randomized clinical trials have demonstrated the diagnostic and prognostic value of coronary computed tomography angiography (CCTA). Advances in CT scanner technology and developments of analytic tools now enable accurate quantification of coronary artery disease (CAD), including total coronary plaque volume and low attenuation plaque volume. The primary aim of CONFIRM2, (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is to perform comprehensive quantification of CCTA findings, including coronary, non-coronary cardiac, non-cardiac vascular, non-cardiac findings, and relate them to clinical variables and cardiovascular clinical outcomes.<br />Design: CONFIRM2 is a multicenter, international observational cohort study designed to evaluate multidimensional associations between quantitative phenotype of cardiovascular disease and future adverse clinical outcomes in subjects undergoing clinically indicated CCTA. The targeted population is heterogenous and includes patients undergoing CCTA for atherosclerotic evaluation, valvular heart disease, congenital heart disease or pre-procedural evaluation. Automated software will be utilized for quantification of coronary plaque, stenosis, vascular morphology and cardiac structures for rapid and reproducible tissue characterization. Up to 30,000 patients will be included from up to 50 international multi-continental clinical CCTA sites and followed for 3-4 years.<br />Summary: CONFIRM2 is one of the largest CCTA studies to establish the clinical value of a multiparametric approach to quantify the phenotype of cardiovascular disease by CCTA using automated imaging solutions.<br />Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Alexander R. van Rosendael is a member, Cleerly Scientific Advisory Board. Tami Crabtree is an employee and equity holder, Cleerly, Inc. Gianluca Pontone has received honorarium as speaker/consultant and/or institutional research grant from GE Healthcare, Bracco, Medtronic, Novartis. Ronny R. Buechel reports receiving speaking honoraria from GE Healthcare, Pfizer, Gilead, and IBA. Christoph Gräni received funding from the Swiss National Science foundation, InnoSuisse, CAIM foundation, GAMBIT foundation, Novartis foundation for biomedical research, outside of the submitted work. Andrew D. Choi is a consultant for Siemens, holds equity in Cleerly, and receives grant support from the George Washing Heart and Vascular Institute.Carlos E. Rochitte reports receiving speaking honoraria for Pfizer, Edwards, GE, and Manole. David M. German reports no conflicts Himanshu Gupta reports no conflicts. Omar Khalique is a consultant for Edwards, Croivalve, Restore Medical, holds equity in Triflo, and has received honoraria for educational programs from Heartflow. Udo Hoffmann is an employee and equity holder, Cleerly, Inc., and has received honoraria from Stanford University, Clinical Cardiovascular Sciences, Rapid AI, MedTrace. James Earls is an employee and equity holder, Cleerly, Inc. James K. Min is an employee and equity holder, Cleerly, Inc. and a member of the Arineta Medical Advisory Board. Ibrahim Danad is a member, Cleerly Scientific Advisory Board. Hugo Marques is a consultant for Cleerly, Inc.<br /> (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1876-861X
- Volume :
- 18
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Journal of cardiovascular computed tomography
- Publication Type :
- Academic Journal
- Accession number :
- 37951725
- Full Text :
- https://doi.org/10.1016/j.jcct.2023.10.004